Job Description:

Job Title: Analytics Manager

About the Role

We are looking for an experienced, hands-on Analytics Manager to build and maintain statistical models, data pipelines, and agentic decision-support solutions. This is a technical, execution-focused role involving direct coding and modeling. Success will require close collaboration with onsite and offshore team members.

Business Translation & Client Engagement

• Work directly with client stakeholders to define business requirements and translate them into simplified, actionable analytical solutions.
• Collaborate with cross-functional and offshore development teams to translate requirements into technical implementation, ensuring clear handoff and shared understanding across the onsite-offshore partnership.
• Translate ad hoc stakeholder requests into structured requirements, clarify scope through direct follow-up, and deliver iterative updates until sign-off.
• Establish key success metrics and translate business priorities into concrete analytical objectives.

Advanced ML & Generative AI

• Build and maintain sales attribution and conversion models across multiple business teams, including logic for measuring overlap and channel contribution.
• Design and implement LLM-based solutions, including vector search/embedding-based retrieval and agent-style automation.
• Support and harden AI-driven workflow agents in production, including automated event logging and recovery to ensure reliability.
• Conduct exploratory data analysis and statistically compare model alternatives under documented core assumptions.

Technical Execution (SQL/Python/BI)

• Write efficient SQL (BigQuery) and build data transformation workflows in Python.
• Validate and reconcile pricing and transaction-level data against source systems to identify and resolve discrepancies.
• Build and maintain rollup dashboards and reporting views that consolidate performance data for leadership review cycles.
• Deliver descriptive analytics and diagnostic dashboards using Tableau and lightweight web applications (Google Apps Script, JavaScript).
• Maintain data pipelines and cloud architecture (Google Cloud Platform / BigQuery) for streamlined ad-hoc analysis.
• Conduct code reviews and audit processes to maintain strict reporting accuracy.

Retail/CPG Domain Expertise

• Perform product and transaction-level analysis supporting material to inventory matching.
• Analyze conversion and performance metrics including project- or category-level breakdowns.
• Apply familiarity with core commercial metrics (conversion rate, pricing and inventory accuracy, SLA performance) to domain-specific analytical problems.

Leadership & Mentorship

• Work in a self-driven and collaborative manner within a team environment.
• Mentor junior team members and contribute to knowledge-sharing initiatives.
• Support automation and reporting consistency across a distributed team by maintaining shared documentation and QA processes.

What We're Looking For

Qualifications

• Bachelor's or Master's degree in Data Science, Computer Science, Mathematics, Statistics, Business Analytics, or a related field.
• 6-8 years of experience in advanced analytics, data science, machine learning, or a related field, with demonstrated hands-on ownership of production models and client-facing delivery.

Technical Skills:

• Languages & Scripting: Expert proficiency in SQL and Python; working proficiency in JavaScript and Google Apps Script for lightweight application/reporting tools.
• Analytics & Data Warehousing: Advanced experience with Google Cloud Infrastructure (BigQuery), data architecture design, and data warehousing.
• BI & Visualization: Tableau; experience building custom dashboards/web apps using Google Apps Script and JavaScript.
• Methodologies: Statistical modeling, significance testing, exploratory data analysis, and predictive frameworks.
• AI/GenAI: Familiarity with LLM-based frameworks, vector databases, and agentic AI development practices.

Soft Skills & Domain Knowledge:

• Ability to translate stakeholder input into clear analytical requirements.
• Ability to explain complex quantitative concepts to non-technical business audiences.
• Comfortable working across onsite-offshore team structures.

At dentsu, we believe great work happens when we’re connected. Our way of working combines flexibility with in-person collaboration to spark ideas and strengthen our teams. Employees who live within a commutable distance of one of our hub offices, currently located in Chicago, metro Detroit, Los Angeles, and New York City, are required and expected to work from the office three days per week (two days per week for employees based in Los Angeles). Dentsu may designate other Hub offices at any time. Those who live outside a commutable range may be designated as remote, depending on the role and business needs. Regardless of your work location, we expect our employees to be flexible to meet the needs of our Company and clients, which may include attendance in an office.

The annual salary range for this position is $94,000-$160,000. Placement within the salary range is based on a variety of factors, including relevant experience, knowledge, skills, and other factors permitted by law.  

Benefits available with this position include:  

• Medical, vision, and dental insurance, 

• Life insurance,  

• Short-term and long-term disability insurance, 

• 401k, 

• Flexible paid time off, 

• At least 15 paid holidays per year, 

• Paid sick and safe leave, and 

• Paid parental leave. 

Dentsu also complies with applicable state and local laws regarding employee leave benefits, including, but not limited to providing time off pursuant to the Colorado Healthy Families and Workplaces Act, in accordance with its plans and policies.  For further details regarding Dentsu benefits, please visit www.dentsubenefitsplus.com. 

To begin the application process, please click on the “Apply” button at the top of this job posting. Applications will be reviewed on an ongoing basis, and qualified candidates will be contacted for next steps. 

#LI-MS3 #LI-Remote

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